Ed Zitron with his subpar takes again.
You could kill all the major AI labs today, and even just today's open-weight models are enough to absolutely transform society, with video-game GPU stuck together at homes.
From what I've seen lately, Ed isn't saying the technology isn't significant. He criticizes the fact that AI companies are dumping this kind of money into it with circular financing deals. If it goes like you say, (GPUs at home) the AI labs will be destroyed, because no one will need the inference capacity they're dumping money into when they can do the decent part at home. From what I've seen he says it's more "not worth the investment" rather than not a breakthrough. It just sucks compared to the trillions they're spending which they'll never recover, is the argument. But I guess it's easier to strawman the argument to "this stuff isn't going to change anything".
He is saying technology isnt significant. Again and again and he puts a lot of emphasis on it. He is also focusing the circular financing deals, on it being a bubble etc.
Obviously, you can agree with one thing and not with other. And he can be right in one thing and not the other. But, if you listen to what he is saying, he is absolutely saying the technology is not significant.
I think you're misinterpreting a strongly worded "it isn't as great as the hype" with "there's nothing there". Because "nothing there that matches the hype" is both 100% true and completely different than "nothing there".
I don't think I am misinterpreting him. I did read some of his articles and did listened to some of his podcasts.
He is very very clear and open on what he thinks about usefulness of ai. He is not saying "it isn't as great as the hype". He is saying "it is useless". He is simply not the centrist kind of guy when it comes to AI usefulness.
The larger 3.5 quants are actually pretty close to the full-blown 397B model's performance, at least looking at the numbers. Qwen 3.5 seems more tolerant of quantization than most.
I think you missed the point, he doesn't disagree with your points at all, he's just pointing out that you shouldn't stress yourself out thinking you have to win them all when actually 1 is often all you need.
I’m not sure if the author’s perspective aligns with what I said.
> You don’t need every job to choose you. You just need the one that’s the right fit.
I don’t think anyone expects to pass all the interviews. Seriously, who expects that? The right fit of choices is often limited. You need to deeply understand your weaknesses and strengths to even know what the right fit is. People are usually unaware of their own superpowers. Hard work is the only thing that pays off. Luck comes to those who are prepared.
Of course tradition has no real merit on its own, but studying the same linguistic tradition is what enables two people to communicate by using language. Unless you manage to complete John Wilkins's project, perhaps, and eliminate the arbitrariness of Wilkins's decisions.
However, in this conversation, we are speaking English, whose words owe their meaning entirely to tradition.
And the word "word" used to mean "to speak", as in make a sound. The word "merit" likely meant "to assign". Current day meaning matters a lot more than what something used to be.
